To me the most useful part of this somewhat skimpy book is the table of features of Cassandra. Usefully placed at the start, in chapter 1. It shows at a glance the items, with their antecedants in Google BigTable and Amazon Dynamo. The chapter provides a succinct recap of the basic ideas behind those 2 commercial approaches. We get the big picture of the CAP theorem. This provides the theoretical context for understanding BigTable, Dynamo and Cassandra itself. Granted, some readers will be frustrated with the modica of details furnished in the chapter. You may have to use this to extract search terms and look online for more information. The remainder of the text delves into the Cassandra patterns for efficient writes and reads. Well, it is a change from most books on general purpose design patterns. Those cited here are indeed specialised. This is the book's value. It's not about generic patterns. One particular pattern is intriguing. How to integrate with higher level analytics. Cassandra is motivated primarily for real time transactions. Analytics is typically and necessarily batch oriented. Too computationally intensive to do in anything approaching real time. Well, turns out one pattern lets you link to Hadoop, which is strong at those batch analytics. But the discussion of this is frustratingly sparse. More could have been written here.